Dynamic determination of filters for flight search results

ABSTRACT

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing travel itinerary filters. In one aspect, a method includes receiving a flight query including a plurality of parameters; determining a plurality of itineraries that satisfy the parameters of the flight query; clustering the plurality of itineraries into a plurality of clusters, wherein the clusters depend upon values of particular features of the plurality of itineraries that satisfy the flight query, and wherein each cluster is generated to have particular values for one or more features of a plurality of features; generating one or more filters corresponding to one or more of the clusters, wherein each filter has the particular values of the one or more features identified by the corresponding cluster; and providing the plurality of itineraries that satisfy the flight query and the one or more filters for filtering the plurality of itineraries.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 14/519,918 filed Oct. 21, 2014 and entitled“Dynamic Determination of Filters for Flight Search Results.” Thecomplete disclosure of the above-identified priority application ishereby fully incorporated herein by reference.

BACKGROUND

This specification relates to information retrieval.

Conventional online travel booking sites allow users to identify andpurchase travel according to a specified itinerary. For example, a usermay use a flight search tool to view flight itineraries that matchflight search parameters such as origin location, destination location,and travel dates. The user can select and purchase a flight itinerarythat best matches the user's preferences. Typically, following thepurchase of a particular flight itinerary, the user will follow theflight itinerary and complete the trip.

SUMMARY

This specification describes technologies relating to providing filtersfor travel itineraries.

In general, one innovative aspect of the subject matter described inthis specification can be embodied in methods that include the actionsof receiving a flight search query, the flight search query including aplurality of parameters; determining a plurality of itineraries thatsatisfy the parameters of the flight search query; clustering theplurality of itineraries into a plurality of clusters, wherein theclusters depend upon values of particular features of the plurality ofitineraries that satisfy the flight search query, and wherein eachcluster is generated to have particular values for one or more featuresof a plurality of features; generating one or more filters correspondingto one or more of the clusters, wherein each filter has the particularvalues of the one or more features identified by the correspondingcluster; and providing, for presentation on a user device, the pluralityof itineraries that satisfy the flight search query and the one or morefilters for filtering the plurality of itineraries. Other embodiments ofthis aspect include corresponding computer systems, apparatus, andcomputer programs recorded on one or more computer storage devices, eachconfigured to perform the actions of the methods. A system of one ormore computers can be configured to perform particular operations oractions by virtue of having software, firmware, hardware, or acombination of them installed on the system that in operation causes orcause the system to perform the actions. One or more computer programscan be configured to perform particular operations or actions by virtueof including instructions that, when executed by data processingapparatus, cause the apparatus to perform the actions.

The foregoing and other embodiments can each optionally include one ormore of the following features, alone or in combination. Each itineraryof the plurality of itineraries is a member of at least one cluster. Theparticular values of the one or more features of each cluster have anassociated weight. Each cluster has an associated quality score.Generating the one or more filters using the clusters includes selectingone or more clusters having a highest associated quality score. Theclustering includes assigning a feature vector to each itinerary andclustering based on the feature vectors. The flight search queryincludes values for origin location, destination location, and dateparameters. The one or more features include one or more of price,duration, number-of stops, airline, or departure time. The methodfurther includes receiving input from the user device indicating aselection of one or more filters; and re-clustering the itineraries ofthe plurality of itineraries that satisfy the selected filters.

Particular embodiments of the subject matter described in thisspecification can be implemented so as to realize one or more of thefollowing advantages. A set of dynamic filters can be automaticallypresented to a flight search user. Dynamic flight search filters canallow the user to see meaningful division points between a large numberof flight search results. The filters are tailored to the specificflight search to provide filters that are helpful for the particularcontext of the search. The user is able to determine particular featuresabout the available flight itineraries by viewing the presented filters.The generated filters having one or more specific parameters allow auser to more quickly identify appropriate flights without applying anumber of standard filters to the available flight itineraries.

The details of one or more embodiments of the subject matter describedin this specification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages of thesubject matter will become apparent from the description, the drawings,and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example environment for providingfilters for filtering flight itineraries.

FIG. 2 is a block diagram of an example environment that includes atravel system.

FIG. 3 is a block diagram of an example travel system.

FIG. 4 is a flow diagram of an example method for providing filters forfiltering flight itineraries.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

A user can submit a flight search query to a travel system. The flightsearch query can include, particular search parameters such as originlocation, destination location, departure date, and return date. Thetravel system can identify a set of flight itineraries that satisfy thereceived search parameters. The travel system can cluster the identifieditineraries into a set of clusters, with the itineraries in a givencluster having values for one or more itinerary features, such as price,duration, number of stops, or carrier that are the same or within aspecified range. One or more filters can be generated using the clustersand the identified itineraries and the generated filters can be providedto a user device of the user for display, e.g., in a travel searchinterface. The user can use the filters to filter the itinerariesresponsive to the flight search query. The filters can indicategroupings of itineraries that may be meaningful to the user and that mayotherwise not be obvious to the user.

For situations in which the systems discussed here collect informationabout users, or may make use of information about users, the users maybe provided with an opportunity to control whether programs or featurescollect user information (e.g., information about a user's socialnetwork, social actions or activities, profession, demographics, auser's preferences, or a user's current location), or to control whetherand/or how to receive content from a content server that may be morerelevant to the user. In addition, certain data may be treated in one ormore ways before it is stored or used, so that certain information aboutthe user is removed. For example, a user's identity may be treated sothat no identifying information can be determined for the user, or auser's geographic location may be generalized where location informationis obtained (such as to a city, ZIP code, or state level), so that aparticular location of a user cannot be determined. Thus, the user mayhave control over how information about the user is collected and usedby a content server.

FIG. 1 is a block diagram of an example environment 100 for providingfilters for filtering flight itineraries. The example environment 100includes a network 102, such as a local area network (LAN), a wide areanetwork (WAN), the Internet, or a combination thereof. The network 102connects user devices 104 to a travel system 106. The exampleenvironment 100 may include many user devices 104, which can each beassociated with one or more users.

A user device 104 is an electronic device that is under control of auser and is capable of requesting and receiving resources over thenetwork 102. Example user devices 104 include personal computers, tabletcomputers, mobile communication devices (e.g., smartphones),televisions, set top boxes, personal digital assistants and othersuitable devices that can send and receive data over the network 102. Auser device 104 typically includes one or more user applications, suchas a web browser, to facilitate the sending and receiving of data overthe network 102. A user of a user device 104 can, for example, use a webbrowser to search for a particular travel itinerary, including a flightitinerary.

The travel system 106 can receive a flight search query 112 from a userdevice 104. The flight search query 112 can include one or moreparameters, such as values for origin location, destination location,and date parameters. In some implementations, the flight search query112 is input to a flight search interface that includes respectivefields for inputting parameter values. In some other implementations,the flight search query 112 is a free text query to a search field thatincludes values for the one or more parameters. The origin anddestination locations can identify cities or particular airports.

The travel system 106 can query flight information 110 to determine aplurality of matching itineraries 114 that satisfy the parameters of theflight search query 112. The flight information 110 can be, for example,flight information received from a cache of flight information that isperiodically updated, flight information received from each carrier, orflight information received as aggregated from carriers by anothersystem.

The travel system 106 can provide the matching itineraries 114 to theuser device with a set of standard filters that the user can selectivelyenable/disable. Enabling a filter can result in reducing a presentedlist of itineraries by removing all itineraries which don't satisfy thefilter condition. For example, enabling a “Carrier A” filter can resultin the removing of all itineraries that are not on “Carrier A”. Asanother example, enabling a “nonstop” filter can result in the removingof all itineraries which involve stopping at an intermediate airport.Standard filters can include filtering by airline, price, flightduration, nonstop, or number of stops, to name a few examples. A usermay be able to provide input individually selecting one or more of thefilters.

The matching itineraries 114 can include, for example, hundreds (ormore) of flight itineraries. Using standard filters to narrow down thematching itineraries into a manageable set so as to select an itinerarythat most satisfies the user can be a long trial-and-error process. Theuser may not be able to determine which standard filters willconveniently or meaningfully divide up the matching itineraries 114.Desirable itineraries, including perhaps a best flight itinerary for theuser, can be easily and mistakenly excluded by the application of astandard filter. Also, a user may not know how to best articulate theirpreferences using standard filters, or may not have the patience fortrial-and-error standard filter experimentation.

As an alternative or an addition to standard filters, the travel system106 can create and provide a set of filters that are generated based offa clustering of the matching itineraries 114. That is, instead of or inaddition to presenting a set of standard filters that are common to eachflight search, machine learning/optimization techniques can be used toautomatically select and present a small set of pre-configured filtersthat may be the most useful in the context of the flight search query112 for dividing the matching itineraries 114. The matching itineraries114 can be described, for example, as a disjunction of clusters whereeach cluster has particular values for one or more features, such asprice, duration, number-of stops, airline, or departure time. The set ofclusters can summarize the matching itineraries 114 to the user so thatthe user can quickly view itinerary information for making an informedselection, knowing that they have found the best itinerary and have notaccidentally overlooked or filtered out the best itinerary.

The travel system 106 clusters the matching itineraries 114 into aplurality of clusters 116. Each cluster of the clusters 116 hasparticular values for one or more features of a plurality of features.Features can include, for example, price, duration, number-of stops,airline, or departure time. An example cluster can represent “flights oncarrier A that are less than $500, have at most one stop, and are lessthan four hours”. The clusters 116 can be generated so that eachitinerary of the matching itineraries 114 is a member of at least onecluster of the clusters 116.

The travel system 106 can generate one or more filters 118 using theclusters 116. For example, a filter can be created for each of theclusters 116 that filters based on the values of the one or morefeatures of the cluster. Each of the filters 118, for example, can haveassociated presentation text (e.g., “flights on carrier A that are lessthan $500, have at most one stop, and are less than four hours”, asdescribed above). Each of the filters 118 can have or can be associatedwith a set of logical expressions or conditions that can be applied tothe matching itineraries 114 to produce a subset of itineraries thatmatch the filter.

The matching itineraries 114 that satisfy the flight search query 112and the filters 118 can be provided to the user device 104, forpresentation on a display of the user device 104. For example, theitineraries 114 can be presented in an itinerary list in a travel searchinterface. The presentation text of some or all of the filters 118 canbe presented, for example, adjacent to the itinerary list. The filterscan be configured to be selected in response to a selection input, e.g.,from a user. For example, the user can select the presentation text of arespective filter to filter the itinerary list. In response to aselection input, the presented itineraries can be modified to show asubset of the itineraries 114 that match the selected filter. The usercan select, for example, an itinerary presented in the subsetteditinerary list to view more information about the itinerary, obtaininformation on purchasing the itinerary through a booking provider, etc.

FIG. 2 is a block diagram of an example environment 200 that includes atravel system 202. A user 204 uses a user device 206 to submit a flightsearch query 208 to the travel system 202. For example, the user 204 canuse a search interface 210 to configure search parameters included inthe flight search query 208 of an origin destination of BOS, adestination location of ZRH, a departure date of Jun. 29, 2014, and areturn date of Jul. 2, 2014, using user interface controls 212, 214,216, and 218, respectively.

The travel system 202 can determine a set of itineraries that match thesearch parameters included in the flight search query 208. The travelsystem 202 can cluster the itineraries into a set of clusters, with eachcluster having particular values for one or more features such as price,duration, or number of stops, to name a few examples. The travel system202 can generate one or more filters using the clusters and can providethe itineraries and generated filters (e.g., as illustrated byitineraries and filters 220) to the user device 206.

The itineraries can be shown, for example, in an itinerary list 222. Insome implementations, a specified number of itineraries are displayed(e.g., five) in the travel search interface 210. In someimplementations, the number of itineraries that are displayed is basedon available display space in the travel search interface 210. In someimplementations, the user 204 can scroll to see itineraries other thanthose initially visible.

The filters provided to the user device 206 can be presented in thesearch interface 210. For example, the search interface 210 includesfilters 224, 226, 228, and 230. The user 204 can select one or morefilters 224-230 to cause the itinerary list 222 to show only itinerariesthat match the selected filter(s). For example, the user 204 can selectthe filter 224 to see flight itineraries that cost as little as $1531,are at least forty four hours, and have at least four segments. Asanother example, the user 204 can select the filter 226 to view flightitineraries that cost as little as $1928, are as short as twenty onehours, and have four segments, two of which are on Carrier A. The user204 can select the filter 228 to view flight itineraries that cost aslittle as $1928, are as short as twenty one hours, and have foursegments, two of which are on Carrier B. The user 204 can select thefilter 230 to view flight itineraries that cost as little as $2569, areas short as fifteen hours, and have one segment on Carrier C. The travelsearch interface 210 can optionally include other filters such as thestandard filters described above with respect to FIG. 1.

As another example, a user 234 uses a user device 236 to submit a flightsearch query 238 to the travel system 202. For example, the user 234 canuse a search interface 240 to configure search parameters included inthe flight search query 238 of an origin destination of MSP, adestination location of ATL, a departure date of Jun. 29, 2014, and areturn date of Jul. 3, 2014, using user interface controls 242, 244,246, and 248, respectively. The travel system 202 can determine a set ofitineraries that match the search parameters included in the flightsearch query 238, cluster the itineraries into a set of one or moreclusters, generate one or more filters using the clusters and providethe itineraries and filters (e.g., as illustrated by itineraries andfilters 250) to the user device 236.

In some implementations and as shown in the search interface 240, afilter can be displayed along with a list of itineraries that match thefilter. For example, an itinerary list 250 is displayed underneath afilter 252. The filter 252 is associated with flight itineraries thatinclude nonstop flights from $500 that have a duration of three hours.The itinerary list 250 can include a subset of flight itineraries thatmatch the filter 252. A “see all” link 254 can be selected to view allof the itineraries that match the filter 252.

Other examples include an itinerary list 256 displayed underneath afilter 258 and an itinerary 260 displayed underneath a filter 262. Thefilter 258 is associated with flight itineraries on Carrier A, with aduration of 4.5 hours, with one stop, and costing from $400. The filter262 is associated with flight itineraries having two or more stops,lasting at least 5.5 hours, costing from $360.

In some implementations, such as on displays of mobile devices, a filterlist can be displayed without initially displaying any matchingitineraries. The user can select a filter in the filter list to viewitineraries that match the selected filter. For example, a filter list270 is displayed in a search interface 272 on a user device 274 of auser 276 in response to a flight search query 278. The filter list 270includes a filter 280 representing flights costing at least $550, afilter 282 representing flights on Carrier B with one stop, lasting atleast 5.5 hours and costing from $430, and a filter 284 representingflights on Carrier C that depart at 6:20 am and cost from $410. The user276 can select a filter 280, 282, or 284 to view flight itinerariesassociated with the selected filter. The filter list 270 conciselydisplays the choices that the user 276 has regarding selecting a flightitinerary. The user 276 may, for example, have to either pay at least$550, take a non-direct flight, or take an early flight (e.g., at 6:20am).

FIG. 3 is a block diagram of an example travel system 300. In stage 1, auser interface engine 302 receives a flight search query 304 (e.g., froma user device). The flight search query 304 includes values for one ormore parameters, such as values for an origin location, a destinationlocation, and date parameters.

In stage 2, an itinerary finder 306 determines a plurality ofitineraries 307 that satisfy the parameters of the flight search query304. The itinerary finder 306 can, for example, query flight information308. The flight information 308 can be, for example, flight informationreceived from a cache of flight information that is periodicallyupdated, flight information received from each carrier, or flightinformation received as aggregated from carriers by another system.

In stage 3, a cluster generator 310 clusters the itineraries 307 into aset of clusters 312. Each of the clusters 312 (e.g., including a cluster312 a) has particular values for one or more features of a collection offeatures. For instance, the cluster 312 a has a collection 314 offeature/value pairs. Features can include, for example, one or more ofprice, duration, number-of stops, airline, or departure time. In someimplementations, some or all of the values in the collection 314 offeature/value pairs have an associated weight. As described in moredetail below, each of the clusters 312 can have an associated qualityscore (e.g., the cluster 312 a has a quality score 316). The clustergenerator 310 can assign a feature vector to each of the itineraries 307(e.g., an itinerary 307 a has a feature vector 318) and cluster theitineraries 307 based on the feature vectors.

In stage 4, a filter generator 320 generates one or more filters 322using the clusters 312. In some implementations, the filter generator320 generates the filters 322 from a subset of the clusters 312 thathave the highest associated quality scores. For example, a filter can begenerated for each of a specified number (e.g., five) of thehighest-scoring clusters. In some implementations, the number of filtersgenerated is based at least in part on whether the respective clustershave a quality score that exceeds a threshold value.

In stage 5, the user interface engine 302 provides the itineraries 307that satisfy the flight search query 304 and the one or more filters 322to the user device that submitted the flight search query for display.The filters 322 are configured for selection in response to a receivedinput and therefore can be selected by the user, for example, to filter(e.g., view a subset of) the itineraries 307 on the user device.

The travel system 300 can include other components. For example, in someimplementations, the travel system 300 can include a repository ofcached common flight search queries and associated, pregenerated filtersthat can be retrieved when a cached, common flight search query isreceived. The repository can be updated periodically, such as once anhour or once per day. A list of the common flight search queries can bemaintained based on ongoing analysis of received flight search queries

FIG. 4 is flow diagram of an example method 400 for filtering flightitineraries. For convenience, the method 400 will be described withrespect to a system, including one or more computing devices, thatperforms the method 400.

The system receives a flight search query including a plurality ofparameters (step 402). For example, a flight search query can bereceived from a user device. The flight search query can include, forexample, values for origin location, destination location, date, orother parameters

The system determines a set of itineraries that satisfy the parametersof the flight search query (step 404). For example, a database and/or adata feed of current flight information can be queried to determineitineraries that satisfy the parameters of the flight search query.

The itineraries are clustered into a group of clusters (step 406), eachcluster having particular values for one or more features of acollection of features. The one or more features can includepredetermined features such as price, duration, number-of stops,airline, or departure time, for example. Clusters can be generated sothat each itinerary is a member of at least one cluster.

In some implementations, a feature vector is determined for eachitinerary. The feature vector can include, for an itinerary, an elementfor each feature in a set of features. The features in the set offeatures can include, for example, the predetermined features mentionedabove and/or other features identified from the itineraries. In someimplementations, a weight is assigned to each element in a featurevector to facilitate feature vector comparison. Weights for somefeatures, such as price, duration, and number of stops, can beassociated, for example, with a non-personalized best-flights model.Other features, which may be subjective (e.g., “is on Carrier A”, or“departs before 9 am”), can be weighted so that they appear in a clusterwhen they are a feature that distinguishes a cluster from otherclusters.

In some implementations, a quality score can be determined for andassociated with each cluster. For example, a quality score of a clustercan represent a user's confidence in applying a filter associated withthe cluster and understanding what itineraries are being excluded usingthe filter. For example a “costs less than $2000” cluster can have ahigher quality score than a “costs less than $500” cluster, andsimilarly a “flight less than 12 hours” cluster can have a higherquality score than a “flight less than 9 hours” cluster. Clustersassociated with features that do not have continuous values (e.g.,“Carrier A”, “is nonstop”) can have a fixed, predetermined qualityscore. In some implementations, the quality of a cluster can be definedusing formula (1):Σ_(1≤i≤l) min_(s∈cluster)(f _(i)(s))  (1)where f_(i) ranges across all features in a feature vector associatedwith the cluster, s ranges across all itineraries in the cluster,f_(i)(s) denotes the value of feature f_(i) for itinerary s, andmin_(s∈cluster)(f_(i)(s)) is the least value of feature f_(i) for anyitinerary in the cluster. The least values are summed across allfeatures f_(i) in the feature vector to determine the quality score forthe cluster.

As mentioned above, a cluster can have more than one feature. A highquality cluster can be a cluster that has at least one high-scoringfeature for which every itinerary in the cluster scores highly.Accordingly, high-quality clusters can be described concisely anddistinctively by using a description that indicates the high-scoringfeature(s) and, if applicable, a threshold value associated with thefeature (e.g., a high-scoring feature can be described as “flightscosting at least $1000”).

In some implementations, the system clusters the itineraries using amixed-integer linear program solving process, with integer-valuedvariables representing cluster assignments. For example, suppose thatthere are t determined itineraries and a target number of n clusters.Accordingly, n X t integer variables can be included in a linearprogram, with an integer variable at a position of (i, s) having a valueof one when an s^(th) solution is in an i^(th) cluster and having avalue of zero when the s^(th) solution is not in the i^(th) cluster. Thelinear program solving process can be configured to determine a solutionin which variable assignments maximize an overall quality score. In someimplementations, the overall quality score for a solution is defined asthe lowest-quality cluster in the solution.

In some other implementations, the overall quality score of a solutionis the average (e.g., weighted mean) quality of the clusters in thesolution, where the mean is weighted by the number of itineraries ineach cluster. Determining an overall quality score within the solvingprocess can include adding one or more real-valued variables to thelinear program. The variable assignments that are output by the linearprogram solving process can be used for determining the clustering.

As another example, the system clusters the itineraries usinghierarchical agglomerative clustering. The system can generate onecluster for each determined itinerary with each initial clusterincluding only the respective itinerary. The system can perform multiplecombination steps, where at each step the system combines a pair ofclusters chosen to maximize a quality score for that step. The qualityscore for a step can be defined, for a pair of clusters C and D that arecombined into a cluster containing both C and D (e.g., a cluster CD), asquality (CD). As another example, the quality score for the step can bedefined as quality (CD)—min(quality(C), quality(D)). The system cancontinue combining clusters (including combining aggregate clusters)until the number of remaining clusters is reduced to a specified numberof clusters (e.g., five).

The system generates one or more filters using the clusters (step 408).Filters can be generated, for example, so that every determineditinerary is rejected by at least one filter. In some implementations, afilter may be generated for each cluster that has a quality score abovea threshold. In some implementations, a filter may be generated for apredetermined number (e.g., five) of the clusters with the highestquality scores.

The system provides the plurality of itineraries that satisfy the flightsearch query and the one or more filters for presentation on a userdevice, for filtering the plurality of itineraries (step 410). Forexample, a user can select a presented filter to view a subset ofitineraries that match the selected filter.

In some implementations, in response to receiving input from the userdevice indicating selection of one or more filters, the itineraries thatsatisfy the selected filters can be re-clustered, and a new set offilters can be generated and presented on the user device. Furthermore,selection of one of the new filters can result in further re-clusteringand presentation of other filters, and so on.

In some implementations, offline analysis of generated clusters can beperformed. For example, market characteristics of a particular type offlight (e.g., New York to Chicago) can be determined by determining thehighest quality clusters for the market for various itineraries that areassociated with the market. For example, the highest quality clusterscan be determined for New York to Chicago flights for various times ofday or days of week and a distribution of clusters and associatedfeatures can be determined. Other analysis for other markets can beperformed, where a market can be defined as a set of itineraries thathave one or more features (e.g., origin destination, locationdestination, carrier, departure time, or other feature) in common.

Embodiments of the subject matter and the operations described in thisspecification can be implemented in digital electronic circuitry, or incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Embodiments of the subject matterdescribed in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on computer storage medium for execution by, or tocontrol the operation of, data processing apparatus. Alternatively or inaddition, the program instructions can be encoded on anartificially-generated propagated signal, e.g., a machine-generatedelectrical, optical, or electromagnetic signal, that is generated toencode information for transmission to suitable receiver apparatus forexecution by a data processing apparatus. A computer storage medium canbe, or be included in, a computer-readable storage device, acomputer-readable storage substrate, a random or serial access memoryarray or device, or a combination of one or more of them. Moreover,while a computer storage medium is not a propagated signal, a computerstorage medium can be a source or destination of computer programinstructions encoded in an artificially-generated propagated signal. Thecomputer storage medium can also be, or be included in, one or moreseparate physical components or media (e.g., multiple CDs, disks, orother storage devices).

The operations described in this specification can be implemented asoperations performed by a data processing apparatus on data stored onone or more computer-readable storage devices or received from othersources.

The term “data processing apparatus” encompasses all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing The apparatus can includespecial purpose logic circuitry, e.g., an FPGA (field programmable gatearray) or an ASIC (application-specific integrated circuit). Theapparatus can also include, in addition to hardware, code that createsan execution environment for the computer program in question, e.g.,code that constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.The apparatus and execution environment can realize various differentcomputing model infrastructures, such as web services, distributedcomputing and grid computing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored in a portion of a file that holds other programsor data (e.g., one or more scripts stored in a markup languagedocument), in a single file dedicated to the program in question, or inmultiple coordinated files (e.g., files that store one or more modules,sub-programs, or portions of code). A computer program can be deployedto be executed on one computer or on multiple computers that are locatedat one site or distributed across multiple sites and interconnected by acommunication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory ora random access memory or both. The essential elements of a computer area processor for performing actions in accordance with instructions andone or more memory devices for storing instructions and data. Generally,a computer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto-optical disks, or optical disks.However, a computer need not have such devices. Moreover, a computer canbe embedded in another device, e.g., a mobile telephone, a personaldigital assistant (PDA), a mobile audio or video player, a game console,a Global Positioning System (GPS) receiver, or a portable storage device(e.g., a universal serial bus (USB) flash drive), to name just a few.Devices suitable for storing computer program instructions and datainclude all forms of non-volatile memory, media and memory devices,including by way of example semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic disks, e.g., internal harddisks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., a CRT (cathode ray tube) or LCD (liquidcrystal display) monitor, for displaying information to the user and akeyboard and a pointing device, e.g., a mouse or a trackball, by whichthe user can provide input to the computer. Other kinds of devices canbe used to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, ortactile input. In addition, a computer can interact with a user bysending documents to and receiving documents from a device that is usedby the user; for example, by sending web pages to a web browser on auser's client device in response to requests received from the webbrowser.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back-end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front-end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back-end, middleware, or front-end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinventions or of what may be claimed, but rather as descriptions offeatures specific to particular embodiments of particular inventions.Certain features that are described in this specification in the contextof separate embodiments can also be implemented in combination in asingle embodiment. Conversely, various features that are described inthe context of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

Thus, particular embodiments of the subject matter have been described.Other embodiments are within the scope of the following claims. In somecases, the actions recited in the claims can be performed in a differentorder and still achieve desirable results. In addition, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults. In certain implementations, multitasking and parallelprocessing may be advantageous.

What is claimed is:
 1. A method to provide graphical user interfaces comprising filtered flight itineraries, comprising: by a flight search computing system: clustering a plurality of itineraries that satisfy parameters of a flight search query into a plurality of clusters based on values of one or more features of each of the plurality of itineraries, wherein each of the plurality of clusters comprises particular values for each of the one or more features; generating one or more primary filters corresponding to one or more of the plurality of clusters, wherein each primary filter has respective particular values of the one or more features of the corresponding cluster; transmitting, to a user computing device, instructions to display a graphical user interface comprising the plurality of itineraries that satisfy the flight search query and to display data that describes the one or more primary filters, the instructions configured to display, for at least one of the one or more primary filters, respective particular values for at least two features of the one or more features; receiving, from the user computing device, an input from the user computing device, a selection of at least one of the one or more primary filters in the graphical user interface; and in response to receiving the selection of the at least one of the one or more primary filters in the graphical user interface, re-clustering, at least one of the plurality of itineraries that satisfy the selected at least one of the one or more primary filters to generate one or more secondary filters in the graphical user interface.
 2. The method of claim 1, wherein each of the plurality of itineraries is a member of at least one cluster.
 3. The method of claim 1, wherein each of the particular values of the one or more features of each cluster of the plurality of clusters comprises an associated weight.
 4. The method of claim 1, wherein each of the plurality of clusters comprises an associated quality score.
 5. The method of claim 4, wherein generating the one or more primary filters using the plurality of clusters comprises selecting, by the flight search computing system, one or more clusters having a highest associated quality score.
 6. The method of claim 1, further comprising, by the flight search computing system, assigning a feature vector to each of the plurality of itineraries, and wherein clustering the plurality of itineraries into the plurality of clusters comprises clustering the plurality of itineraries into the plurality of clusters based on the one or more assigned feature vectors.
 7. The method of claim 1, wherein the parameters comprise one or more of an origin location, a destination location, and date parameters.
 8. The method of claim 1, wherein the one or more features comprise one or more of a price, a duration, a number of stops, an airline, and a departure time.
 9. The method of claim 1, wherein the selection comprises an in input to the user computing device.
 10. The method of claim 1, further comprising, by the flight search computing system, transmitting, to the user computing device, instructions to update the display of the graphical user interface to display the one or more secondary filters and itineraries that satisfy the selected one or more primary filters.
 11. The method of claim 1, further comprising, by the flight search computing system, receiving, from the user computing device, the flight search query comprising the parameters.
 12. A system to provide graphical user interfaces comprising filtered flight itineraries, comprising: a storage device; and one or more computers configured to execute application code instructions stored in the storage device to cause the system to: cluster a plurality of itineraries that satisfy parameters of a flight search query into a plurality of clusters based on values of one or more features of each of the plurality of itineraries, wherein each of the plurality of clusters comprises particular values for each of the one or more features; generate one or more primary filters corresponding to one or more of the plurality of clusters, wherein each primary filter has respective particular values of the one or more features of the corresponding cluster; transmit, to a user computing device, instructions to display a graphical user interface comprising the plurality of itineraries that satisfy the flight search query and to display data that describes the one or more primary filters, the instructions configured to display, for at least one of the one or more primary filters, respective particular values for at least two features of the one or more features; receive, from the user computing device, a selection of at least one of the one or more primary filters in the graphical user interface; and in response to receiving the selection of the at least one of the one or more primary filters in the graphical user interface, re-cluster at least one of the plurality of itineraries that satisfy the selected at least one of the one or more primary filters to generate one or more secondary filters in the graphical user interface.
 13. The system of claim 12, wherein each of the plurality of itineraries is a member of at least one cluster.
 14. The system of claim 12, wherein each of the particular values of the one or more features of each of the plurality of clusters comprises an associated weight.
 15. The system of claim 12, wherein each of the plurality of clusters comprises an associated quality score.
 16. The system of claim 12, wherein generating the one or more primary filters using the plurality of clusters comprises selecting one or more clusters having a highest associated quality score.
 17. The system of claim 12, wherein the one or more computers are further configured to execute application code instructions stored in the storage device to cause the system to assign a feature vector to each of the plurality of itineraries, wherein clustering the plurality of itineraries into the plurality of clusters comprises clustering the plurality of itineraries into the plurality of clusters based on one or more assigned feature vectors.
 18. A non-transitory computer-readable storage medium encoded with a computer program, comprising computer-executable instructions that when executed by one or more computers cause the one or more computers to provide graphical user interfaces comprising filtered flight itineraries, the computer-executable instructions comprising: computer-executable instructions to cluster a plurality of itineraries that satisfy parameters of a flight search query into a plurality of clusters based on values of one or more features of each of the plurality of itineraries, wherein each of the plurality of clusters comprises particular values for each of the one or more features; computer-executable instructions to generate one or more primary filters corresponding to one or more of the plurality of clusters, wherein each primary filter has respective particular values of the one or more features of the corresponding cluster; computer-executable instructions to transmit, to a user computing device, instructions to display a graphical interface comprising the plurality of itineraries that satisfy the flight search query and to display data that describes the one or more primary filters, the instructions configured to display, for at least one of the one or more primary filters, respective particular values for at least two features of the one or more features; computer-executable instructions to receive, from the user computing device, a selection of at least one of the one or more primary filters in the graphical user interface; and computer-executable instructions to re-cluster, in response to receiving the selection of the at least one of the one or more primary filters in the graphical user interface, at least one of the plurality of itineraries that satisfy the selected at least one of the one or more primary filters to generate one or more secondary filters in the graphical user interface.
 19. The non-transitory computer-readable storage medium of claim 18, wherein each of the plurality of clusters comprises an associated quality score.
 20. The non-transitory computer-readable storage medium of claim 19, wherein generating the one or more primary filters using the plurality of clusters comprises selecting one or more clusters having a highest associated quality score. 